On adaptive estimation in partial linear models

Georgi Golubev and Wolfgang Härdle

No 2000,21, SFB 373 Discussion Papers from Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes

Abstract: We consider a problem of estimation of parametric component in a partial linear model. Suppose that a finite set E of linear estimators is given. Our goal is to mimic the estimator in E that has the smallest risk. Using a second order expansion of the risk of linear estimators we propose a practically feasible adaptive procedure for choke of smoothing parameters based on the principle of unbiased risk estimation.

Date: 2000
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